Systems, apparatuses, and methods for determining locations of wireless nodes in a network architecture are disclosed herein. In one example, a system for localization of nodes in a wireless network architecture comprises a plurality of wireless anchor nodes each having a known location and a wireless device with one or more processing units and RF circuitry for transmitting and receiving communications in the wireless network architecture and a wireless node having a wireless device with a transmitter and a receiver to enable bi-directional communications with the plurality of wireless anchor nodes in the wireless network architecture. One or more processing units of at least one of the plurality of wireless anchor nodes are configured to execute instructions to determine a set of possible ranges between each anchor node and the wireless node having an unknown location and to perform a triangulation algorithm that utilizes a maximum likelihood estimation (MLE) of ranging measurements from anchor nodes.
Legal claims defining the scope of protection, as filed with the USPTO.
1. A system for localization of nodes in a wireless network architecture, comprising: a plurality of wireless anchor nodes each having a known location and a wireless device with one or more processing units and RF circuitry for transmitting and receiving communications in the wireless network architecture; and a wireless node having a wireless device with a transmitter and a receiver to enable bi-directional communications with the plurality of wireless anchor nodes in the wireless network architecture, wherein one or more processing units of at least one of the plurality of wireless anchor nodes are configured to execute instructions to determine a set of possible ranges between each anchor node and the wireless node having an unknown location and to perform a triangulation algorithm that utilizes a maximum likelihood estimation (MLE) of ranging measurements from anchor nodes.
2. The system of claim 1 , wherein the MLE of ranging measurements from anchor nodes is based on a probability distribution for ranging measurements and position hypothesis for each anchor node.
3. The system of claim 2 , wherein the MLE of ranging measurements from anchor nodes is based on an uncertainty in a ranging measurement from the wireless node to an anchor node as determined in the ranging measurement, and a distance from the anchor node to a current position hypothesis.
4. The system of claim 3 , wherein the MLE reduces importance of high uncertainty measurements on overall triangulation estimation by effectively weighting high uncertainty measurements less than other measurements for determining a final location of the wireless node.
5. The system of claim 1 , wherein at least one anchor node to be selected for localization when an error metric that is associated with each distance estimate between an anchor node having a known location and the wireless sensor node having an unknown location is less than or equal to an error threshold.
6. The system of claim 5 , wherein at least one anchor node to be eliminated for localization when the error metric is greater than or equal to the error threshold.
7. The system of claim 1 , wherein at least one of the anchor nodes comprises a moveable robot that changes positions from a first anchor node position to a second anchor node position during localization.
8. An apparatus for localization of nodes in a wireless network architecture, comprising: a memory for storing instructions; one or more processing units to execute instructions for controlling a plurality of wireless sensor nodes in a wireless network architecture and determining locations of the plurality of wireless sensor nodes; and radio frequency (RF) circuitry to transmit communications to and receive communications from the plurality of wireless sensor nodes each having a wireless device with a transmitter and a receiver to enable bi-directional communications with the RF circuitry of the apparatus in the wireless network architecture, wherein the one or more processing units of the apparatus are configured to execute instructions to determine a set of possible ranges between the apparatus and a wireless sensor node having an unknown location and to perform a triangulation algorithm that utilizes a maximum likelihood estimation (MLE) of ranging measurements from anchor nodes including the apparatus.
9. The apparatus of claim 8 , wherein the MLE of ranging measurements from anchor nodes is based on a probability distribution for ranging measurements and position hypothesis for each anchor node.
10. The apparatus of claim 9 , wherein the MLE of ranging measurements from anchor nodes is based on an uncertainty in a ranging measurement from the wireless node to an anchor node as determined in the ranging measurement, and a distance from the anchor node to a current position hypothesis.
11. The apparatus of claim 10 , wherein the MLE reduces importance of high uncertainty measurements on overall triangulation estimation by effectively weighting high uncertainty measurements less than other measurements for determining a final location of the wireless node.
12. The apparatus of claim 8 , wherein the apparatus comprises a moveable robot that changes positions within an indoor environment from a first anchor node position to a second anchor node position during localization.
13. The apparatus of claim 8 , wherein the one or more processing units of the apparatus are configured to execute instructions to measure a first channel state information of a first frequency channel of a RF signal that is received from the wireless sensor node, to measure second channel state information of a second frequency channel of the RF signal with the first and second frequency channels being non-contiguous or discontinuous channels, to determine delay profile estimation between the apparatus and the wireless sensor node based on the first and second channel state information without phase alignment.
14. The apparatus of claim 13 , wherein the delay profile estimation is determined without channel state information for a frequency band gap between the first and second frequency channels.
15. A method for localization of nodes in a wireless network architecture, comprising: transmitting, with a plurality of wireless anchor nodes each having a known location, communications to a wireless node; receiving communications from the wireless node; determining, with at least one anchor node, a set of possible ranges between each anchor node and the wireless node having an unknown location; and performing a triangulation algorithm that utilizes a maximum likelihood estimation (MLE) of ranging measurements from anchor nodes.
16. The method of claim 15 , wherein the MLE of ranging measurements from anchor nodes is based on a probability distribution for ranging measurements and position hypothesis for each anchor node.
17. The method of claim 16 , wherein the MLE of ranging measurements from anchor nodes is based on an uncertainty in a ranging measurement from the wireless node to an anchor node as determined in the ranging measurement, and a distance from the anchor node to a current position hypothesis.
18. The method of claim 17 , wherein the MLE reduces importance of high uncertainty measurements on overall triangulation estimation by effectively weighting high uncertainty measurements less than other measurements for determining a final location of the wireless node.
19. The method of claim 15 , further comprising: selecting at least one anchor node for localization when an error metric that is associated with each distance estimate between an anchor node having a known location and the wireless sensor node having an unknown location is less than or equal to an error threshold.
20. The method of claim 19 , further comprising: eliminating at least one anchor node for localization when the error metric is greater than or equal to the error threshold.
21. The method of claim 15 , wherein at least one of the anchor nodes comprises a moveable robot that changes positions from a first anchor node position to a second anchor node position during localization.
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February 22, 2019
October 13, 2020
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